Taipei, Taiwan

Meng-Han Li


Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2019

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1 patent (USPTO):Explore Patents

Title: Innovations of Meng-Han Li in Physiological Signal Detection

Introduction

Meng-Han Li is an accomplished inventor based in Taipei, Taiwan. He has made significant contributions to the field of physiological signal detection through his innovative methods. His work focuses on improving the accuracy and efficiency of detecting physiological signals in real time.

Latest Patents

Meng-Han Li holds a patent for a non-contact method for detecting physiological signals and motion in real time. This method involves sensing a portion of a human body to generate a series of image frames using an optical sensing element. It determines a complexion region from each image frame and calculates a central coordinate of that region. By expanding a surrounding range from the central coordinate, the method obtains a complexion fluctuation waveform. It then compares the central coordinates of consecutive image frames to calculate displacement over time, determining whether the body part is static. In a static state, the method performs noise filtering and peak detection on the complexion fluctuation waveform to calculate a physiological signal. This innovative approach reduces the amount of data needed for processing and enhances detection accuracy.

Career Highlights

Meng-Han Li is affiliated with National Taiwan University, where he continues to advance his research and development in the field of physiological signal detection. His work has garnered attention for its potential applications in health monitoring and medical diagnostics.

Collaborations

Meng-Han Li collaborates with notable colleagues, including Yuan-Hsiang Lin and Yu-Chen Lin, who contribute to his research endeavors.

Conclusion

Meng-Han Li's innovative contributions to physiological signal detection demonstrate his commitment to advancing technology in healthcare. His patented method showcases the potential for improving accuracy in real-time physiological monitoring.

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